作者
Adeleh Yarmohammadi, Linda M Zangwill, Alberto Diniz-Filho, Min Hee Suh, Patricia Isabel Manalastas, Naeem Fatehee, Siamak Yousefi, Akram Belghith, Luke J Saunders, Felipe A Medeiros, David Huang, Robert N Weinreb
发表日期
2016/7/1
期刊
Investigative ophthalmology & visual science
卷号
57
期号
9
页码范围
OCT451-OCT459
出版商
The Association for Research in Vision and Ophthalmology
简介
Purpose: The purpose of this study was to compare retinal nerve fiber layer (RNFL) thickness and optical coherence tomography angiography (OCT-A) retinal vasculature measurements in healthy, glaucoma suspect, and glaucoma patients.
Methods: Two hundred sixty-one eyes of 164 healthy, glaucoma suspect, and open-angle glaucoma (OAG) participants from the Diagnostic Innovations in Glaucoma Study with good quality OCT-A images were included. Retinal vasculature information was summarized as a vessel density map and as vessel density (%), which is the proportion of flowing vessel area over the total area evaluated. Two vessel density measurements extracted from the RNFL were analyzed:(1) circumpapillary vessel density (cpVD) measured in a 750-μm-wide elliptical annulus around the disc and (2) whole image vessel density (wiVD) measured over the entire image. Areas under the receiver operating characteristic curves (AUROC) were used to evaluate diagnostic accuracy.
Results: Age-adjusted mean vessel density was significantly lower in OAG eyes compared with glaucoma suspects and healthy eyes.(cpVD: 55.1±7%, 60.3±5%, and 64.2±3%, respectively; P< 0.001; and wiVD: 46.2±6%, 51.3±5%, and 56.6±3%, respectively; P< 0.001). For differentiating between glaucoma and healthy eyes, the age-adjusted AUROC was highest for wiVD (0.94), followed by RNFL thickness (0.92) and cpVD (0.83). The AUROCs for differentiating between healthy and glaucoma suspect eyes were highest for wiVD (0.70), followed by cpVD (0.65) and RNFL thickness (0.65).
Conclusions: Optical coherence tomography angiography vessel …
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A Yarmohammadi, LM Zangwill, A Diniz-Filho, MH Suh… - Investigative ophthalmology & visual science, 2016